Processing of categorized product information

1. A data processing system, comprising: one or more processors configured to: access a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein: a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters and a plurality of non-product attribute parameters; and the plurality of product attribute parameters comprises standard product information and non-standard product information, wherein the standard product information comprises the plurality of non-product attribute parameters; select, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partition standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information; partition one of the plurality of sets into a plurality of subsets based on one non product attribute parameter of the plurality of non-product attribute parameters; partition the standard product information within one of the plurality of sets into a plurality of subsets based on a degree of similarity of non-product attribute parameters; determine whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning meet an established criterion; deduplicate the standard product information and the non-standard product information; and provide a product recommendation to be displayed by a user based on the plurality of subsets; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions.

2. The system of claim 1 , wherein the representative product attribute parameter was previously used by users to search for products.

3. The system of claim 1 , wherein a set in the plurality of sets includes a product attribute parameter with identical value for all products associated with the set.

4. The system of claim 1 , wherein the processor is further configured to use the plurality of sets to make a product recommendation.

5. The system of claim 1 , wherein the processor is further configured to search the plurality of sets to provide a search result.

6. A data processing system, comprising: one or more processors configured to: access a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein: a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters and a plurality of non-product attribute parameters; and the plurality of product attribute parameters comprises standard product information and non-standard product information, wherein the standard product information comprises the plurality of non-product attribute parameters; select, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; determine a degree of similarity of the non-product attribute parameters; partition standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information; partition one of the plurality of sets into a plurality of subsets based on at least one non-product attribute parameter of the plurality of non-product attribute parameters; partition the standard product information within one of the plurality of sets into a plurality of subsets such that the degree of similarity within each subset meets a first threshold value; determine whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning meet an established criterion; in the event that the values of product attribute parameters that correspond to the non-standard product information and used for set partitioning do not meet the established criterion, determine a subset for which a correlation of the non-product attribute parameters to the non-standard product information meets a second threshold value; and provide a product recommendation to be displayed to a user based on the plurality of subsets.

7. The system of claim 6 , wherein the processor is further configured to: in the event that at least some of the values of product attribute parameters that correspond to the non-standard product information and used for set partitioning meet an established criterion, determine a set to which the non-standard product information belongs based on the at least some of the values of product attribute parameters.

8. The system of claim 7 , wherein the processor is further configured to partition the non-standard product information into a subset of the set to which the non-standard product information belongs.

9. The system of claim 8 , wherein the processor is further configured to deduplicate standard product information and non-standard product information.

10. A data processing method, comprising: accessing a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein: a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters and a plurality of non-product attribute parameters; and the plurality of product attribute parameters comprises standard product information and non-standard product information, wherein the standard product information comprises the plurality of non-product attribute parameters; selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information; partitioning one of the plurality of sets into a plurality of subsets based on one non-product attribute parameter of the plurality of non-product attribute parameters; partitioning the standard product information within one of the plurality of sets into a plurality of subsets based on a degree of similarity of non-product attribute parameters; determining whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning meet an established criterion; deduplicating the standard product information and the non-standard product information; and providing a product recommendation to be displayed by a user based on the plurality of subsets.

11. A computer program product for data processing, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for: accessing a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein: a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters and a plurality of non-product attribute parameters; and the plurality of product attribute parameters comprises standard product information and non-standard product information, wherein the standard product information comprises the plurality of non-product attribute parameters; selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information; partitioning one of the plurality of sets into a plurality of subsets based on one non-product attribute parameter of the plurality of non-product attribute parameters; partitioning the standard product information within one of the plurality of sets into a plurality of subsets based on a degree of similarity of non-product attribute parameters; determining whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning meet an established criterion; deduplicating the standard product information and the non-standard product information; and providing a product recommendation to be displayed by a user based on the plurality of subsets.